Abstract: With the deepening of exploration and development, due to the limitation of the resolution of the conventional seismic data, it is difficult to meet the needs of exploration and development. Since the attenuation degree of different frequency components of seismic signals is different, the frequency decomposing technology can be applied to perform differential compensation on each frequency component to improve the resolution of seismic data. However, the conventional frequency division technology generally not only holds low frequency division accuracy but also shows modal aliasing, thus it cannot be well applied to seismic data processing. To solve these problems, this paper proposes a high-resolution processing method for seismic data based on adaptive variational modal decomposition (VMD). The multi-objective bat algorithm is applied to the variational modal decomposition, and the VMD parameters are optimized by the fitness function constructed using power spectrum entropy, energy difference, and sample entropy. The model test results show that the optimized VMD method holds high frequency division accuracy and strong anti-noise ability, and also can avoids modal aliasing, When the optimized VMD method is applied to high-resolution processing of seismic data, the model and actual data test results show that the resolution of processed seismic data is effectively improved.